similar to: disagreement in loglikelihood and deviace in GLM with weights leads to different models selected using step()

My virtual users have their mail stored in /usr/local/virtual/user at example.com/ dovecot wants to read the mail from /usr/local/virtual/user at example.com/Maildir which is causing problems since all new mail is being written in /usr/local/virtual/user at example.com/new and dovecot is looking in /usr/local/virtual/user at example.com/Maildir/new For the local users, /home/user/Maildir is the

Hi Rers, I have a silly question. I don't know how to express the loglikelihood function of 1/(x!) where x=x1,x2,....xn in R. Could anyone give me a hint? Thank you in advance. Chunhao Tu

Dear R-help, The documentation for systemfit shows that logLik() can be used to obtain loglikelihood values from linear systems estimated by systemfit(). It seems to me that logLik() cannot be used for nlsystemfit(). Does anyone know of any other packages that might let me obtain the loglikelihood of a model estimated with nlsystemfit()? Kind regards, Alex Olssen

Hi, I am trying to learn lognormal mixture models with EM. I was wondering how does one compute the log likelihood. The current implementation I have is as follows, which perform really bad in learning the mixture models. __BEGIN__ # compute probably density of lognormal. dens <- function(lambda, theta, k){ temp<-NULL meanl=theta[1:k] sdl=theta[(k+1):(2*k)]

Hi, I tried to compute maximum likelihood under gamma distribution, using nlm function. The code is this: __BEGIN__ vsamples<- c(103.9, 88.5, 242.9, 206.6, 175.7, 164.4) mlogl <- function(alpha, x) { if (length(alpha) > 1) stop("alpha must be scalar") if (alpha <= 0) stop("alpha must be positive") return(- sum(dgamma(x, shape = alpha, log = TRUE)))

Hi,  I tried fitting loglinear model using the glm(catspec). The data used is FHtab. . An independence model was fitted. Here summary() and fitmacro( ) give different values for AIC.   I understand that fitmacro( ) takes the likelilhood ratio L2(deviance) to calculate AIC and uses the formula AIC= L2- d.f(deviance)*2 and this AIC is used for comparison of nested models. (Am I right?)   The value

Hi - I have a likelihood function that involves sums of two possions: L = a*dpois(Xi,theta1)*dpois(Yi,theta2)+b*(1-c)*a*dpois(Xi,theta1+theta3)*dpois(Yi,theta2) where a,b,c,theta1,theta2,theta3 are parameters to be estimated. (Xi,Yi) are observations. However, Xi and Yi are usually big (> 20000). This causes dpois to returns 0 depending on values of theta1, theta2 and theta3. My first

A user alerted me to a problem when he renamed an upper level mail folder and lost access to a lower level folder under it. I tried with and without listescape, it didn't seem to make a difference, and I saw no errors in the dovecot log. Symptoms are if a client has a maildir folder tree .a and .a.b and renames a to c in their client, Thunderbird shows c/b but b is inaccessible since it

I was asked by my boss to do an analysis on a large data set, and I am trying to convince him to let me use R rather than SPSS. I think Sweave could make my life much much easier. To get me a little closer to this goal, I ran my analysis through R and SPSS and compared the resulting values. In all but one case, they were the same. Given the matrix [,1] [,2] [1,] 110 358 [2,] 71 312 [3,]

Dear R experts, Attached you can find the expression of a loglikelihood function which I would like to maximize in R. So far, I have done maximization with the combined use of the mathematical programming language AMPL (www.ampl.com) and the solver SNOPT (http://www.sbsi-sol-optimize.com/manuals/SNOPT%20Manual.pdf). With these tools, maximization is carried out in a few seconds. I wonder if that

Hi there, I'm trying to solve a ML problem where the likelihood function is a function of two numerical procedures and I'm having some problems figuring out how to do this. The log-likelihood function is of the form L(c,psi) = 1/T sum [log (f(c, psi)) - log(g(c,psi))], where c is a 2xT matrix of data and psi is the parameter vector. f(c, psi) is the transition density which can be

Dear friends - occurring in Windows R2.6.2 I am modeling physical chemistry in collaboration with a friend who has preferred working in Excel. I used uniroot, and find a solution to a two buffer problem in acid-base chemistry which I believe is physiologically sensible. Using "goal seek" in Excel my friend found another plausible root, quite close to zero, and a plot of the function

Dear R users, I am estimating Poisson mixed models using glmmPQL (MASS) and lmer (lme4). We know that glmmPQL do not provide the correct loglikelihood for such models (it gives the loglike of a 'pseudo' or working linear mixed model). I would like to know how the loglike is calculated by lmer. A minor question is: why do glmmPQL and lmer give different degrees-of-freedom for the same

Hi, all. I have a simple design I'm comparing to output from SPSS. the design is 1 repeated measure (session) and 1 between measure (cond). my dependent measure is rl. here is the data I'm using (in a data.frame): mig <- data.frame(subj=factor(rep(subj,3)), cond=factor(rep(cond,3)), session=factor(c(rep(1,nsubj),rep(2,nsubj),rep(3,nsubj))),

It has always been my understanding that deviance for GLMs is defined by; D = -2(loglikelihood(model) - loglikelihood(saturated model)) and this can be calculated by (or at least usually is); D = -2(loglikelihood(model)) As is done so in the code for 'polr' by Brian Ripley (in the package 'MASS') where the -loglikehood is minimised using optim; res <-

Dear R community, I am still new to R, but I am attempting to use it for (hopefully) all my plotting needs. I have been using lattice and Hmisc for most plots so far successfully, but I need help creating a plot I desire for some new data I have. This data frame consists of the same type of measurement (Eh) for 27 different locations. I have 8000+ measurements for each location, and my

Hello, we are using rsync on AIX and run into out of memory. There have been some threads about out of memory and FAX tells that this is a known problem. So I need to finde a workaround for this. Please help me! We try to sync many (nnnn) Thumbnails of size 2k between AIX and Linux with rsync -a --delete --rsh=ssh <source dir> <user>@<server>:<target dir> I

Dear R-list members, Some months ago I wrote a message on the usage of gnls (nlme library) and here I come again. Let me give an example: I have a 10 year length-at-age data set of 10 fishes (see growth.dat at the end of this message) and I want to fit a von Bertalanffy growth model, Li= Linf*(1-exp(-k*(ti-t0))) where Li = length at age i, Linf= asymptotic length, k= curvature parameter, ti=

There appears to be a disagreement between the encoding given in the sources for Siren14 that are downloaded from Polycom (and the ITU, both are the same) and that implemented by codec_siren14.so. The latter agrees with the actual device. If I make a .sln32 file and run the encoder from ITU/Polycom with encode 0 foo.sln32 foo.siren14 48000 14000 the resulting file doesn't play back

I would like to report a working device to add to the hardware compatibility list, but cannot find a way on the website. Would this list be OK for that purpose? Best regards, Ernest